For over a century, antivenoms have relied on serum extraction from animals — a process that’s costly, inconsistent, and limited to specific snake species. Today, advances in synthetic biology and antibody engineering are pointing toward a different future: a universal antivenom capable of neutralizing toxins across the world’s deadliest snakes. This session dives into the science and story behind this breakthrough — from the man who endured more than 200 bites to generate a unique immune response, to the researchers using those antibodies to design broad-spectrum, recombinant therapies. Together, they’re charting the path from survival experiment to programmable immunity.

Join Stanford’s Le Cong for an immersive, hands-on masterclass exploring how CRISPR, genome engineering, and next-generation biological foundation models are converging to redefine programmable biology. This live workshop will walk attendees through CRISPR/GPT — an emerging class of AI-assisted editing frameworks that pair large biological language models with precise genome engineering tools to accelerate design, improve specificity, and unlock new editing modalities. Participants will step inside real CRISPR/GPT workflows to see how multimodal models interpret genomic context, predict repair outcomes, suggest optimized guide designs, and generate editing strategies for complex loci. Le Cong will demonstrate how AI-driven reasoning is beginning to streamline experimental planning, reduce screening burden, and push forward new frontiers in base editing, prime editing, and programmable gene modulation. This session is designed for scientists, engineers, founders, and R&D leaders who want to understand how AI-powered CRISPR design actually works in practice — and how these tools can accelerate therapeutic development, functional genomics, and next-generation editing technologies.

For 20+ years, the synthetic biology community has generated breakthrough targets, but too many continue to stall at the same choke points: freedom-to-operate, productivity, process robustness, CMC readiness, and the leap from “works in the lab” to “works at scale.” In this lightning talk, Ingenza will share how we’ve repeatedly helped teams cross that valley of death, turning innovative discoveries into manufacturable realities across industrial biotech and therapeutics. We’ll spotlight our inGenius® platform: a proven panel of high-performing microbial and mammalian production hosts paired with AI/ML-driven enzyme discovery and gene design optimisation (codABLE®), scalable upstream and downstream platform process workflows, and a comprehensive suite of high-end analytical tools that accelerate and de-risk the path from early discovery to market readiness. Powered by 20+ years of successful delivery, expect rapid, real, case study driven lessons from the front lines: what fails most often, what fixes it fastest, and how to design with manufacturability from day one without slowing innovation. If you’re engineering biology to improve human health or the planet, this talk is your shortcut to faster timelines and better outcomes that help SynBio move at the speed it promises.

Join Boltz co-founder Gabriele Corso for an interactive, hands-on masterclass exploring how next-generation AI models are transforming molecular design, protein engineering, and therapeutic development. In this live workshop, attendees will step inside the Boltz platform to learn how structure-based generative modeling pipelines can be applied to real-world design challenges. Participants will see how AI-driven predictions are reshaping the drug discovery workflow — from identifying high-value molecular hits to optimizing binders, and therapeutic candidates. This session is designed for scientists, founders, and R&D leaders looking to understand how to actually use cutting-edge AI to accelerate biological innovation.

The PURE system, invented 25 years ago, established a fully reconstituted approach to cell-free protein synthesis. What began as a system to better understand translation has evolved into a versatile platform for engineering biology. This talk highlights how PURE-derived platforms such as PUREfrex® enable rapid prototyping, high-throughput screening, and AI/ML-driven optimization, accelerating synthetic biology and next-generation biologics development.

Meat is one of the world’s most complex biomanufacturing systems—and also one of its least optimized. For 12,000 years, we’ve cycled crops through animals to make meat. Drawing from his new book Meat, Bruce Friedrich contends that advances across science and engineering now make it possible to produce meat far more efficiently, which will reduce meat’s contribution to hunger, climate change, deforestation, antibiotic resistance, and pandemic risk. Most importantly for the success of alternative meats, these new technologies will also improve food security and add to GDP for the nations that lean in. It’s been exactly ten years since the first plant-based burgers were introduced and also exactly ten years since the first cultivated meat companies were incorporated. Bruce will reflect on how far we’ve come, how far we have to go, and what it's going to take to get there. Welcome to the next agricultural revolution—courtesy of science.

For decades, pharmaceutical supply chains were optimized for cost and scale, stretching across continents to source critical active ingredients. But fragility has made resilience a strategic imperative. Synthetic biology offers a new model: onshoring the production of essential APIs by programming cells to manufacture small molecules, peptides, and novel amino acids with precision and scalability. Instead of relying on distant chemical supply networks, biology becomes the factory—flexible, distributed, and programmable. This session explores how engineered microbes and directed evolution platforms are rebuilding pharma supply chains from the molecular level up, enabling secure, responsive, and locally anchored production of the medicines the world depends on.

The next frontier of biology isn’t in predicting a single static protein structure, but in capturing how proteins move, fold, and interact across time and environments. This session explores how AI can illuminate protein conformations and dynamics, and extend those insights into virtual multi-cellular or tissue models. Experts will discuss the challenge of integrating heterogeneous datasets and instruments, and how breakthroughs in dynamic modeling could reshape drug design, disease understanding, and biomanufacturing. Can we build models that reflect the living, breathing complexity of biology—not just snapshots, but motion?

Scaling bio-based products requires integrated technical collaboration across strain engineering, fermentation, downstream processing, and analytics. Full-stack approaches—where startups, CDMOs, and platform technology providers align early on—can optimize yield, reduce variability, and lower cost of goods (COGS) at commercial scale. This session explores case studies of cross-company collaboration, from co-development of microbial strains and bioreactor designs to shared process analytics and predictive modeling. Hear how teams are breaking down technical silos to accelerate scale-up, improve reproducibility, and create competitive, sustainable manufacturing solutions that bring synthetic biology products from the lab to the market efficiently.

Mining has long relied on brute force and chemistry, but biology is opening a new frontier. Biomining uses engineered microbes to extract metals and minerals with precision, efficiency, and far less environmental impact than traditional methods. From rare earth elements essential to clean energy to critical metals powering electronics, synthetic biology is reshaping how we source the building blocks of modern life. This session spotlights innovators designing bio-based recovery systems, scaling sustainable solutions, and reimagining resource extraction.

Why do so many in silico models fail when moved to the lab or clinic? Too often, they’re trained on incomplete, non-human, or non-representative datasets. This session tackles the “data gap” head-on: from interoperability bottlenecks and the black box problem to the limits of current virtual cell simulations (~50 million perturbations vs. the billions biology demands). Panelists will explore how to create “human-first” datasets that reflect real biology, unlock mechanistic interoperability, and close the discovery–development divide. The goal: build AI tools that can directly identify viable drug candidates instead of stalling in silico.

Industrial biotech faces repeated “valleys of death” between laboratory success and commercial manufacturing, driven by a combination of technological uncertainty, scale-dependent constraints, and (mis)alignment between engineering reality and investment expectations. Promising technologies often fail not because the science is wrong, but because scale-up trajectories are built on insufficient data, optimistic assumptions, and decision-making based on the 1st product specifications from the lab that do not translate to industrial conditions. This panel returns to fundamentals, drawing on real-world experience from piloting, process engineering, and early industrialization to examine where and why scale-up breaks down. Experts will discuss how important the scale-up journey is to align technology performance with investor expectations, support sound business cases, and turn the industrial biotech toolbox into a more robust, scalable, and profitable manufacturing platform.